Distributed building deformation detection method based on periodic micro-nano structure

Abstract

The invention discloses a distributed building deformation detection method based on a periodic micro-nano structure. The method comprises the following steps: S1, manufacturing a photonic crystal; s2, the photonic crystal is attached to the surface of the building through flexible epoxy resin, and curing is conducted; s3, the unmanned aerial vehicle gets close to the photonic crystal to collect the reflected spectral signals; and S4, calculating the deformation of the building through the spectrum mapping model. The device has the following beneficial effects: non-contact measurement of surface deformation of a building structure is realized, and damage to a main body structure is avoided; the measurement cost is lower than the traditional measurement cost, and the measurement precision is greatly improved compared with the traditional method and reaches the micron level (+ / -0.5 mu m); the device adapts to reliable work in high-temperature (-40 DEG C to 85 DEG C), high-humidity (0%-95% RH) and strong electromagnetic field environments; the method is suitable for non-contact health monitoring of metal structures such as steel structure bridges and high-rise building steel frames.

Description

Technical Field

[0001] This invention relates to a method for detecting building deformation, and more particularly to a distributed method for detecting building deformation based on periodic micro-nano structures, belonging to the field of intelligent sensing and remote sensing technology. Background Technology

[0002] Existing building deformation detection technologies mainly include: 1) Contact sensors (such as strain gauges and fiber optic sensors): These need to be directly attached to the structural surface, which has problems such as destructive installation (drilling leads to secondary stress concentration) and poor long-term stability (annual drift >5μm).

[0003] 2) Laser scanning technology (such as lidar, 3D modeling): The cost of a single measurement can be as high as tens of thousands of yuan, the minimum resolution is at the millimeter level, and it is easily affected by ambient light interference (signal-to-noise ratio <10dB).

[0004] 3) Unmanned aerial vehicle (UAV) visual inspection: Relies on manually set reference objects, and the measurement accuracy is significantly affected by temperature and humidity (the deformation error increases by 0.8μm for every 1°C change in temperature).

[0005] However, the above-mentioned detection technologies have the following technical defects in practical use: 1) Installation of contact sensors requires damaging the surface of the structure, and the wiring is complex and difficult to achieve large-area coverage; 2) Laser scanning technology is expensive and lacks sufficient sensitivity, making it unable to detect micron-level deformation; 3) The visual inspection of the drone fails in strong light, rain and fog environments, and the data synchronization error rate reaches ±5%. Summary of the Invention

[0006] To address the shortcomings of the aforementioned technologies, this invention provides a distributed building deformation detection method based on periodic micro / nano structures.

[0007] To solve the above technical problems, the technical solution adopted by this invention is: a distributed building deformation detection method based on periodic micro / nano structures, comprising the following steps: Step S1: Fabrication of photonic crystal: After fabricating a photomask, nanostructure transfer is performed to obtain a photonic crystal; Step S2: Attach the photonic crystal to the surface of the building using flexible epoxy resin and then cure it. Step S3: The drone approaches the photonic crystal to collect the reflected spectral signal; Step S4: Calculate the deformation of the building using a spectral mapping model.

[0008] Preferably, in step S1, a mask is fabricated using helium ion beam lithography, specifically including the following steps: Step S11: Spin-coat 495 PMMA A2 photoresist at a speed of 500-2000 RPM to prepare a 50-200 nm thin film, and then spin-coat it at a speed of 500-300 nm. ◦ Preheat the food on the hot plate for 50-200 seconds; Step S12: Use a helium ion microscope to focus a helium ion beam at 10-35kV to expose nanopatterns in a 600 µm × 600 µm area. The exposed pattern consists of 1500 rectangles of the same size, each 600 µm long and with a given width. Step S13: During helium ion beam exposure, the helium ion current is 0.1-1.5 pA, a helium ion beam aperture with a diameter of 5-20 µm is used, the spot size is 5, the dwell time is 0.2-2 s, and the exposure dose is 0.1-1.5 ions / nm. 2 ; After helium ion exposure, the exposed photoresist is immersed in 20-100 ml of a mixture of isopropanol and deionized water in a 7:3 volume ratio at room temperature and mixed for 3-15 minutes to dissolve the exposed PMMA and present the PMMA nanogrid structure.

[0009] Preferably, in step S1, the nanostructure transfer includes the following steps: Step S14: Copy the surface of the PMMA nanogrid onto the UV-cured epoxy resin material; Step S15: Coat the top of the mask with liquid UV-curable epoxy resin polymer and expose it to ultraviolet light. The mask is cross-linked by ultraviolet radiation. The UV-cured epoxy polymer is cured to form a negative patterned nanograting structure and is peeled off from the mold to obtain a photonic crystal. Step S16: Sputter a 10-200 nm thick TiO2 film onto a UV-curable epoxy resin material to serve as a light confinement layer on a photonic crystal plate.

[0010] Preferably, in step S2, the thickness of the flexible epoxy resin is ≤20μm, and the curing time is 12-72 hours.

[0011] Preferably, the specific process of step S3 is as follows: the drone carrying the light source and spectrometer is brought close to the photonic crystal, and the drone is accurately positioned by the alignment mark preset on the photonic crystal. The light source carried by the drone will illuminate the photonic crystal, and the reflected spectral signal will be collected by the spectrometer.

[0012] Preferably, in step S4, the calculation process of the spectral signal in the spectral mapping model is as follows: I. Pre-calibration stage: Establish the model foundation and determine the sensitivity coefficient k; II. Measured Calculation Stage: On-site data conversion, from spectral signals to deformation; Preferably, the pre-calibration stage includes the following steps: Step A1: Prepare standard test samples: Select a photonic crystal consistent with the one prepared in step S1, attach it to the surface of a standard metal specimen, and cure it under the following conditions: 0.1-10N pressure, 12-72 hours. Step A2: Apply controllable strain and acquire the corresponding spectral signal: Place the standard metal specimen on a high-precision tensile testing machine and apply known axial strain in stages under a standard environment of 25°C and 50% RH. After each strain is applied, the same type of light source and spectrometer as those on the drone are used to collect the reflection spectrum signal of the photonic crystal and record the spectral peak wavelength corresponding to each strain. Step A3: Fit a linear relationship and calculate the k value; For each set of spectral peak wavelength data, calculate the peak offset: Δλᵢ = λᵢ - λ0, where λᵢ is the peak wavelength corresponding to strain εᵢ, and λ0 is the reference wavelength without strain; Using strain ε as the abscissa and peak offset Δλ as the ordinate, a linear regression is performed to obtain the fitting equation: Δλ = k·ε, where the slope k is the sensitivity coefficient.

[0013] Preferably, during the actual measurement and calculation phase, and during on-site monitoring, the building deformation is calculated based on the calibrated k value through the following steps: Step 1: Acquire reference spectral signal: When the building structure has not deformed, use a spectrometer mounted on a drone to collect the reflection spectral signal of the photonic crystal and determine the reference peak wavelength λ0. Step 2: Acquire spectral signal after deformation: After the building deforms, repeat the operation of step 1, acquire the reflection spectral signal of the photonic crystal at this time, and extract the peak wavelength λ1 after deformation; Step 3: Calculate the peak offset Δλ; calculate using the following formula: Δλ = λ1 - λ0; Step 4: Substitute into the model to calculate the building deformation: Based on the linear equation Δλ = k・ε obtained in the calibration stage, calculate the strain: ε = Δλ / k.

[0014] Preferably, in step 4, if bidirectional deformation is being monitored, the sensitivity coefficients k in the X and Y directions need to be calibrated separately. x , kᵧ, corresponds to the spectral peak shift Δλ in two directions. x , Δλᵧ, calculate ε respectively x =Δλ x / k x εᵧ=Δλᵧ / kᵧ, and finally synthesize bidirectional deformation data.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. By contacting the building structure surface with a photonic crystal to react to surface deformation, the UAV spectral measurement does not need to contact the building surface (spectral non-destructive non-contact measurement), realizing non-contact measurement of the building structure surface deformation and avoiding damage to the main structure; 2. The measurement cost is lower than that of traditional measurement methods, and the measurement accuracy reaches the micrometer level (±0.5μm) by measuring the peak wavelength of the spectrum. 3. The spectral measurement method based on photonic crystals is not affected by high temperature, high humidity, strong electromagnetic fields, etc., so it can work reliably in high temperature (-40℃~85℃), high humidity (0%-95%RH) and strong electromagnetic field environments; it is suitable for non-contact health monitoring of metal structures such as steel structure bridges and high-rise building steel frames. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the process of the present invention.

[0017] Figure 2 This is a flowchart illustrating the fabrication process of the photonic crystal of this invention.

[0018] Figure 3 This is a schematic diagram of the working operation of the photonic crystal of the present invention. Detailed Implementation

[0019] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0020] The working principle of this invention is as follows: photonic crystals are attached or affixed to the surface of a building to achieve non-contact measurement of the deformation of the building structure, avoiding damage to the main structure. Utilizing the wavelength-selective reflection characteristics of the photonic crystals, the deformation of the building is converted into a spectral displacement signal through a light source and spectrometer mounted on a drone. The measurement cost is lower than that of traditional measurement methods, and the measurement accuracy reaches the micrometer level (±0.5μm). The deformation of the building is obtained through changes in the spectrum (the spectral signal measurement is not affected by high temperature (-40℃~85℃), high humidity (0%-95%RH), or strong electromagnetic field environment, so it is reliable).

[0021] This application introduces optical precision measurement methods into the measurement of building surface deformation. A photonic crystal is non-destructively attached to the building surface, converting the building's deformation into a spectral displacement signal, thereby achieving high-precision, low-cost measurement. Introducing spectral precision measurement into the field of UAV-based building surface deformation detection improves traditional building measurement techniques.

[0022] like Figure 1 The distributed building deformation detection method based on periodic micro / nano structures, as shown, includes the following steps: The fabrication process of photonic crystals is as follows: I. Mask Creation: Currently, there are various methods for mask nanolithography, including focused ion beam lithography, electron beam lithography, scanning probe lithography, and helium ion lithography.

[0023] Compared to existing photolithography methods, helium ion lithography has the following two advantages: 1. Helium ion beam lithography uses helium ions, which have a mass much larger than electrons (approximately 7 × 10³ times that of electrons) and a shorter de Broglie wavelength, thus reducing diffraction effects. This technique employs a smaller aperture design, effectively suppressing spherical aberration and angular broadening of the helium ion beam. Therefore, it can achieve a smaller beam spot size and higher processing precision.

[0024] 2. Under similar energy conditions, helium ions have higher momentum and can resist space charge effects, resulting in smaller surface interaction volumes and lower energy loss. This smaller beam size and higher surface sensitivity significantly reduce the proximity effect in helium ion beam lithography, enabling high-resolution lithography fabrication of nanopatterns with better fidelity and resolution.

[0025] Therefore, this application selects helium ion beam lithography as the mask processing method, such as Figure 2 As shown, the specific steps include: Step 1: Spin-coat a 100 nm thin film with 495 PMMA A2 photoresist at a speed of 1000 RPM, and then spin-coat at 180°C. ◦ Bake on the hot plate for 90 seconds. (Example:) Figure 2 As shown in (a).

[0026] Step 2: Expose nanopatterns within a 600 µm × 600 µm area using a helium ion microscope (OrionFab, Zeiss) with a focused helium ion beam at 30 kV. The exposed pattern consists of 1500 identical rectangles, each 600 µm long and with a specified width. Figure 2 As shown in (b).

[0027] Step 3: During exposure, the helium ion current is 0.2 pA (using an aperture of 10 µm in diameter, a spot size of 5, and the dwell time and dose can be selected as needed; for example, in this work, the dwell time is 1.2 s and the exposure dose is 0.18 ions / nm). 2(Dosage). After helium ion exposure, the sample was immersed in 50 ml of a 7:3 volume ratio mixture of isopropanol and deionized water at room temperature for 5 minutes to dissolve the exposed PMMA (polymethyl methacrylate) and reveal the PMMA nanogrid structure. Figure 2 As shown in (c).

[0028] II. Nanostructure Transfer: Step 1: Copy the surface of the PMMA nanogrid onto a UV (ultraviolet light) cured epoxy resin material. For example... Figure 2 As shown in (d).

[0029] Step 2: A liquid UV-curable epoxy polymer is coated onto the top of a photomask and exposed to ultraviolet light. Once cross-linked by UV radiation, the UV-cured epoxy polymer solidifies to form a negative patterned nanograting structure, which is then peeled off from the mold to obtain a photonic crystal structure. Figure 2 As shown in (e).

[0030] Step 3: Finally, apply an 86 nm thick layer of TiO2. 2 A thin film is sputtered onto a UV epoxy resin structure to serve as a light confinement layer on a photonic crystal substrate. For example... Figure 2 As shown in (f).

[0031] The process for detecting building deformation is as follows: Step 1: Attach the photonic crystal to the surface of the building using flexible epoxy resin (thickness ≤20μm) and cure for 24 hours to prevent it from peeling off. Deformation of the building will cause the photonic crystal to deform, thus altering the reflected spectrum.

[0032] Step 2: Bring the drone carrying the light source and spectrometer close to the photonic crystal attached to the building. Use the pre-set alignment marks on the photonic crystal (which only need to meet the minimum requirements for drone image recognition) to accurately position the drone. The light source carried by the drone will shine on the photonic crystal, and the reflected spectral signal will be collected by the spectrometer.

[0033] Step 3: Calculate the deformation of the building using a spectral mapping model.

[0034] Specifically, the spectral mapping model refers to establishing a linear relationship between strain (ε) and the peak shift (Δλx, Δλy) of the reflectance spectrum through laboratory tensile testing. Here, Δλ = k·ε (where k is the sensitivity coefficient).

[0035] The detailed calculation process of the spectral signal in the spectral mapping model is as follows: The core of the spectral mapping model is to convert the collected spectral signals into strain (deformation) data of the building structure through a linear relationship calibrated in the laboratory. The specific calculation process is divided into a calibration stage and a field measurement calculation stage, which are closely linked. 1. Pre-calibration stage: Establish the model foundation and determine the sensitivity coefficient k; The purpose of this stage is to establish a quantitative relationship between strain (ε) and the peak shift (Δλ) of the reflectance spectrum through controlled experiments, which is a prerequisite for subsequent experimental calculations. Step 1: Prepare standard test samples; Select a photonic crystal consistent with that used in the actual project and attach it to the surface of a standard metal specimen (the material is consistent with the building structure to be monitored, such as steel used in steel bridges). The curing conditions are the same as those in the actual project (0.5N pressure, 24 hours curing).

[0036] Step 2: Apply controllable strain and acquire spectral signals; The standard specimen is placed on a high-precision tensile testing machine, and known axial strain is applied in stages under a standard environment of 25°C and 50% RH (this is part of the test calibration process, where the signal correspondence is obtained using controllable known conditions).

[0037] After each strain is applied, the same type of light source and spectrometer as those on the drone are used to collect the reflection spectrum signal of the photonic crystal and record the spectral peak wavelength corresponding to each strain.

[0038] Step 3: Fit a linear relationship and calculate the k value; For each set of data, calculate the peak offset: Δλᵢ = λᵢ - λ0, where λᵢ is the peak wavelength corresponding to strain εᵢ, and λ0 is the reference wavelength without strain.

[0039] Using strain ε as the abscissa and peak offset Δλ as the ordinate, a linear regression is performed to obtain the fitting equation: Δλ = k·ε, where the slope k is the sensitivity coefficient.

[0040] 2. Measured Calculation Stage: On-site data conversion, from spectral signals to deformation; During on-site monitoring, based on the calibrated k value, the building deformation is calculated through the following steps: Step 1: Acquire the reference spectral signal; When the building structure is not deformed, the reflectance spectrum signal of the photonic crystal is collected by a spectrometer mounted on a drone to determine the reference peak wavelength λ0.

[0041] Step 2: Acquire the spectral signal after deformation; After the building deforms, repeat step 1 to collect the reflection spectrum signal of the photonic crystal at this time and extract the peak wavelength λ1 after deformation.

[0042] Step 3: Calculate the peak offset Δλ; Calculate using the formula: Δλ = λ1 - λ0; Step 4: Substitute the data into the model to calculate strain (deformation); Based on the linear equation Δλ = k・ε obtained during the calibration phase, the strain is calculated as: ε = Δλ / k.

[0043] If monitoring bidirectional deformation (X-axis and Y-axis), the sensitivity coefficients k in the X and Y directions need to be calibrated separately. x , kᵧ, corresponds to the spectral peak shift Δλ in two directions. x , Δλᵧ, calculate ε respectively x =Δλ x / k x εᵧ=Δλᵧ / kᵧ, and finally synthesize bidirectional deformation data.

[0044] The peak shift in the reflectance spectrum is correlated with the spectral signal; the two represent the relationship between the core feature and the original data. The specific correlation is as follows: 1. Spectral signal: This is the raw data collected by the UAV spectrometer. Essentially, it is the "wavelength-intensity" distribution curve of the light reflected by the photonic crystal, which contains intensity information of all reflected light.

[0045] 2. Reflectance spectral peak shift: This is a core feature parameter extracted from the spectral signal (the value of the reflection spectral peak shift). Due to their periodic micro- and nano-structures, photonic crystals exhibit sharp characteristic peaks in their reflection spectra. When structural deformation causes changes in the lattice arrangement of the photonic crystal, the wavelength position of these characteristic peaks shifts. This shift in wavelength position is known as the reflection spectrum peak shift (Δλ = λ1 - λ0).

[0046] 3. Correlation Logic: The spectral signal is the basis for extracting the peak shift. The peak shift is the key information in the spectral signal that is directly related to the deformation. Other spectral information may be affected by ambient light, distance, etc., but the peak shift is only determined by the lattice deformation of the photonic crystal. Therefore, the model only selects this feature (peak shift) for calculation to ensure anti-interference and accuracy.

[0047] Figure 3 λ1 and λ2 are the peak wavelengths of the reflected spectra from two different directions (or different monitoring points). Their core function is to reduce background noise and amplify the measurement signal by comparing the difference between the signals in the two orthogonal directions x and y, thereby accurately calculating the deformation in the corresponding direction. The specific explanation is as follows: 1. Symbol definition (in combination) Figure 3 (Note) λ0: The reference peak wavelength of the photonic crystal in both X and Y directions when there is no deformation (initial state, no offset in both directions); λ1: The peak wavelength of the reflection spectrum in the X direction after deformation; λ2: The peak wavelength of the reflection spectrum in the Y direction after deformation.

[0048] 2. Specific process: Step 1: Calculate the bidirectional peak offset; X-direction offset: Δλ1 = λ1 - λ0; Y-direction offset: Δλ2 = λ2 - λ0.

[0049] Step 2: Correlate bidirectional strain; Figure 3 In the equation (Δλ1-Δλ2) ∝ Strain of X, the expression is simplified; the actual logic is as follows: 1. When the deformation is isotropic (e.g., background noise, ambient temperature and humidity), the changes in the x and y directions are uniform, so the changes in λ1 and λ2 are the same. Therefore, (Δλ1-Δλ2) will be reduced during the calculation due to isotropic changes caused by natural conditions such as background temperature and humidity. This eliminates the influence of background noise on the signal in the spectral testing method, improves the signal-to-noise ratio of the measurement signal, and enhances the system sensitivity.

[0050] 2. Since the deformations in the X and Y directions are orthogonal, and the grating structure is also orthogonal, a deformation in one direction will create two opposite moduli (x and y anisotropy) in the two directions respectively. Therefore, when performing the (Δλ1-Δλ2) calculation, the difference will be automatically compared, directly amplifying the signal in a single direction, thereby further improving the signal-to-noise ratio of the measurement signal and enhancing the system sensitivity. The model has been calibrated k. x 、kᵧ,therefore: X-direction strain ε x = Δλ1 / k x The strain in the Y direction is εᵧ = Δλ2 / kᵧ.

[0051] The above embodiments are not intended to limit the present invention, and the present invention is not limited to the examples given above. Any changes, modifications, additions or substitutions made by those skilled in the art within the scope of the technical solution of the present invention are also within the protection scope of the present invention.

Claims

1. A distributed building deformation detection method based on periodic micro / nano structures, characterized in that: Includes the following steps: Step S1: Fabrication of photonic crystal: After fabricating a photomask, nanostructure transfer is performed to obtain a photonic crystal; Step S2: Attach the photonic crystal to the surface of the building using flexible epoxy resin and then cure it. Step S3: The drone approaches the photonic crystal to collect the reflected spectral signal; Step S4: Calculate the deformation of the building using a spectral mapping model.

2. The distributed building deformation detection method based on periodic micro / nano structures according to claim 1, characterized in that: In step S1, a mask is fabricated using helium ion beam lithography, which specifically includes the following steps: Step S11: Spin-coat 495 PMMA A2 photoresist at a speed of 500-2000 RPM to prepare a 50-200 nm thin film, and then spin-coat it at a speed of 500-300 nm. ◦ Preheat the food on the hot plate for 50-200 seconds; Step S12: Use a helium ion microscope to focus a helium ion beam at 10-35kV to expose nanopatterns in a 600 µm × 600 µm area. The exposed pattern consists of 1500 rectangles of the same size, each 600 µm long and with a given width. Step S13: During helium ion beam exposure, the helium ion current is 0.1-1.5 pA, a helium ion beam aperture with a diameter of 5-20 µm is used, the spot size is 5, the dwell time is 0.2-2 s, and the exposure dose is 0.1-1.5 ions / nm. 2 ; After helium ion exposure, the exposed photoresist is immersed in 20-100 ml of a mixture of isopropanol and deionized water in a 7:3 volume ratio at room temperature and mixed for 3-15 minutes to dissolve the exposed PMMA and present the PMMA nanogrid structure.

3. The distributed building deformation detection method based on periodic micro / nano structures according to claim 1, characterized in that: In step S1, the nanostructure transfer includes the following steps: Step S14: Copy the surface of the PMMA nanogrid onto the UV-cured epoxy resin material; Step S15: Coat the top of the mask with liquid UV-curable epoxy resin polymer and expose it to ultraviolet light. The mask is cross-linked by ultraviolet radiation. The UV-cured epoxy polymer is cured to form a negative patterned nanograting structure and is peeled off from the mold to obtain a photonic crystal. Step S16: Sputter a 10-200 nm thick TiO2 film onto a UV-curable epoxy resin material to serve as a light confinement layer on a photonic crystal plate.

4. The distributed building deformation detection method based on periodic micro / nano structures according to claim 1, characterized in that: In step S2, the thickness of the flexible epoxy resin is ≤20μm, and the curing time is 12-72 hours.

5. The preparation method of the distributed building deformation detection method based on periodic micro / nano structures according to claim 1, characterized in that: The specific process of step S3 is as follows: the drone carrying the light source and spectrometer is brought close to the photonic crystal, and the drone is accurately positioned by the alignment marks preset on the photonic crystal. The light source carried by the drone will illuminate the photonic crystal, and the reflected spectral signal will be collected by the spectrometer.

6. The preparation method of the distributed building deformation detection method based on periodic micro / nano structures according to claim 1, characterized in that: In step S4, the calculation process of the spectral signal in the spectral mapping model is as follows: I. Pre-calibration stage: Establish the model foundation and determine the sensitivity coefficient k; II. Measured Calculation Stage: On-site data conversion, from spectral signals to deformation.

7. The preparation method of the distributed building deformation detection method based on periodic micro / nano structures according to claim 6, characterized in that: The pre-calibration stage includes the following steps: Step A1: Prepare standard test samples: Select a photonic crystal consistent with the one prepared in step S1, attach it to the surface of a standard metal specimen, and cure it under the following conditions: 0.1-10N pressure, 12-72 hours. Step A2: Apply controllable strain and acquire the corresponding spectral signal: Place the standard metal specimen on a high-precision tensile testing machine and apply known axial strain in stages under a standard environment of 25°C and 50% RH. After each strain is applied, the same type of light source and spectrometer as those on the drone are used to collect the reflection spectrum signal of the photonic crystal and record the spectral peak wavelength corresponding to each strain. Step A3: Fit a linear relationship and calculate the k value; For each set of spectral peak wavelength data, calculate the peak offset: Δλᵢ = λᵢ - λ0, where λᵢ is the peak wavelength corresponding to strain εᵢ, and λ0 is the reference wavelength without strain; Using strain ε as the abscissa and peak offset Δλ as the ordinate, a linear regression is performed to obtain the fitting equation: Δλ = k·ε, where the slope k is the sensitivity coefficient.

8. The preparation method of the distributed building deformation detection method based on periodic micro / nano structures according to claim 6, characterized in that: During the actual measurement and calculation phase, and during on-site monitoring, the building deformation is calculated based on the calibrated k value through the following steps: Step 1: Acquire reference spectral signal: When the building structure has not deformed, use a spectrometer mounted on a drone to collect the reflection spectral signal of the photonic crystal and determine the reference peak wavelength λ0. Step 2: Acquire spectral signal after deformation: After the building deforms, repeat the operation of step 1, acquire the reflection spectral signal of the photonic crystal at this time, and extract the peak wavelength λ1 after deformation; Step 3: Calculate the peak offset Δλ; Calculate using the following formula: Δλ = λ1 - λ0; Step 4: Substitute into the model to calculate the building deformation: Based on the linear equation Δλ = k・ε obtained in the calibration stage, calculate the strain: ε = Δλ / k.

9. The preparation method of the distributed building deformation detection method based on periodic micro / nano structures according to claim 8, characterized in that: In step 4, if bidirectional deformation is being monitored, the sensitivity coefficients k in the X and Y directions need to be calibrated separately. x , kᵧ, corresponds to the spectral peak shift Δλ in two directions. x , Δλᵧ, calculate ε respectively x =Δλ x / k x εᵧ=Δλᵧ / kᵧ, and finally synthesize bidirectional deformation data.

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